Solves the inverse problem: find the parameters which most closely appoximate the option prices available in the market. Requires specification of a characeteristic function. Some useful characteristic functions are provided in the cf_functions repository. This module works by fitting a monotonic spline to transformed option data from the market. Then the empirical characteristic function is estimated from the spline. A mean squared optimization problem is then solved in complex space between the analytical characteristic function and the empirical characteristic function. For more documentation and results, see fang_oost_cal_charts. Currently this module only works on a single maturity at atime. It does not calibrate across all maturities simultanously.
Returns transformed strikes. Used to transform the option prices for spline fitting.
Returns iterator over discrete empirical characteristic function
Returns spline function
Returns function which computes the mean squared error between the empirical and analytical characteristic functions for a vector of parameters.
Returns function which computes the mean squared error between the empirical and analytical option prices.
Returns scaled prices